Image-guided radiation therapy (IGRT) can potentially increase treatment effectiveness for tumors of the lower abdomen and lungs that undergo respiration-induced motion. However, its success largely depends upon an adequate understanding of tumor motion characteristics and accurate prediction of tumor position at some point in the future. Such predictions constitute a challenging problem since respiration-induced tumor motion is complicated and patient-specific. Particularly challenging are patients having advanced lung disease or who have highly compromised breathing. Their tumor's motion may be highly erratic with non-uniform period and amplitude, et cetera. The overall objective of the work proposed in this application is to improve the radiation treatment of moving lung tumors. There are two specific aims under this proposal. The first specific aim covers the behavior analysis of tumor motion and patient breathing. The motion of a tumor will be mathematically characterized by defining parameters that categorize its movement with time during a treatment fraction and also cumulatively over the course of the treatment. Individual patient breathing behavior will be modeled by defining motion properties (e.g., amplitude, frequency, velocity) and their relationships between various breathing states (e.g. exhale, inhale, end of exhale) under various patient biomedical (such as anatomical and physiological) conditions. The second specific aim covers the development of a predictive model for tumor motion. A statistical model for predicting future movement behavior of a tumor based on previous motion patterns will be built and dynamically adjusted during real-time radiation treatment. A Hidden Markov Model with weighted probabilities will be explored. The model is expected to accurately predict respiratory-induced tumor motion to allow for true real-time IGRT. The proposed research is innovative since respiration-induced tumor motion has not been fully characterized and the prediction of tumor motion in various parts of the lung is difficult. Our interdisciplinary team of investigators uniquely combines the diverse range of data management, physics support, and clinical expertise needed to reach a definitive outcome for this research. PUBLIC HEALTH RELEVANCE: The proposed research on lung cancer treatment is of great significance since lung cancer is the number one cancer killer in the United States and the five year survival rate is only 15%. The interdisciplinary and translational research described in this proposal will lead to improvement in radiation cancer treatment of moving lung tumors and true real-time image guided radiation therapy (IGRT) for such disease will be made possible.